🛠️ All DevTools

[Other] A universal Price Tracking chrome extension that just works! A universal chrome extension made to track prices across all of the websites with real-time monitoring, historical charts, customizable alerts, and more.

[Other] For Good First Issue – A repository of social impact and open source projects

[Other] Show HN: Dagger.js – A buildless, runtime-only JavaScript micro-framework TL;DR: dagger.js is a buildless, runtime-only micro-framework that plays nicely with native Web Components. It uses HTML-first directives (e.g. +click, +load) so you can ship a page by dropping a single &lt;script&gt; from a CDN—no bundlers, no compile step.<p>Why I built it Modern stacks are powerful but often heavy: bundlers, compile steps, framework DSLs, local CLIs. For internal tools, small apps, and edge&#x2F;serverless deployments, I wanted something you can view-source, paste into a page, and ship.<p>What it is:<p>Runtime-only: no build or VDOM compile; hydrate behaviors directly on HTML. HTML directives: e.g. +click, lifecycle +load &#x2F; +loaded &#x2F; +unload &#x2F; +unloaded. Zero APIs: dagger.js works in pure declarative mode, modules and directives provide everything you need to build your application. Web-Components-first: works alongside Custom Elements; keep concerns local. Distributed modules: load small, focused script modules via CDN. Progressive enhancement: the page renders without a build step.<p>Use cases:<p>Admin panels &amp; dashboards that don’t warrant a full toolchain Embed widgets, docs-sites with interactive bits Edge&#x2F;serverless apps where cold start and simplicity matter<p>Links<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;dagger8224&#x2F;dagger.js" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;dagger8224&#x2F;dagger.js</a> Docs&#x2F;Guide: <a href="https:&#x2F;&#x2F;daggerjs.org" rel="nofollow">https:&#x2F;&#x2F;daggerjs.org</a> Examples: <a href="https:&#x2F;&#x2F;codepen.io&#x2F;dagger8224&#x2F;pens" rel="nofollow">https:&#x2F;&#x2F;codepen.io&#x2F;dagger8224&#x2F;pens</a><p>I’d love feedback on edge-cases, and where it breaks. Happy to answer tough questions here.

[Other] Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems.<p>To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: <a href="https:&#x2F;&#x2F;www.petrostechchronicles.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.petrostechchronicles.com&#x2F;</a>) <a href="https:&#x2F;&#x2F;github.com&#x2F;Aherontas&#x2F;Pycon_Greece_2025_Presentation_Agents" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Aherontas&#x2F;Pycon_Greece_2025_Presentation_...</a><p>The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration.<p>Features:<p>- Multiple agents running in containers<p>- MCP servers (Brave search, GitHub, filesystem, etc.) as tools<p>- A2A communication between services<p>- Minimal UI for experimentation for Tech Trend - repo analysis<p>I built this repo because most agent frameworks look great in isolated demos, but fall apart when you try to glue agents together into a real application. My goal was to help people experiment with these patterns and move closer to real-world use cases.<p>It’s not production-grade, but would love feedback, criticism, or war stories from anyone who’s tried building actual multi-agent systems. Big questions:<p>Do you think agent-to-agent protocols like MCP&#x2F;A2A will stick?<p>Or will the future be mostly single powerful LLMs with plugin stacks?<p>Thanks — excited to hear what the HN crowd thinks!

[Other] DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.

[Other] Show HN: Datadef.io – Canvas for data lineage and metadata management Hi HN, I’ve been working on <a href="https:&#x2F;&#x2F;datadef.io" rel="nofollow">https:&#x2F;&#x2F;datadef.io</a>, a tool to help data team (engineer, architect, project manager) make sense of their data universe.<p>The problem:<p>- Data models (dbt, SQL, warehouses) often grow into a tangled mess of tables, joins, and undocumented assumptions. - Lineage is either scattered across tools or missing entirely. - Documentation is usually an afterthought (and gets outdated fast).<p>Datadef.io aims to fix that by providing:<p>- Interactive canvas to map tables, relationships, and indicators. - Automatic lineage visualization to trace dependencies. - Metadata management: define table&#x2F;column-level details, ownership, and KPIs. - AI-generated documentation that stays in sync with your models. - Export&#x2F;share features so asset managers, analysts, and other teams don’t get lost in spreadsheets or PDFs.<p>It’s still early, and I’d love feedback from the HN community. In particular:<p>What’s missing for you in lineage&#x2F;metadata&#x2F;documentation tools?<p>How would you want to integrate a tool like this into your workflow (dbt, Databricks, Power BI, etc.)?<p>I’d really appreciate your thoughts, feature requests, and criticism.<p>Thanks!

[CLI Tool] docker mcp CLI plugin / MCP Gateway

[DevOps] AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

[API/SDK] A cryptocurrency trading API with more than 100 exchanges in JavaScript / TypeScript / Python / C# / PHP / Go

[Other] Developer-first, enterprise-grade LLM framework. GraphBit is a high-performance AI agent framework with a Rust 🦀 core and seamless Python bindings. It combines Rust’s speed and reliability with Python’s simplicity, empowering developers to build intelligent, enterprise-grade agents with ease.

[API/SDK] Chaos to Clarity. No Code. No Confusion. No Chaos. APITect turns chaos into clarity in API development. 🚀 Paste JSON to get instant contracts, validate in real-time, mock dynamic responses, collaborate with your team & export anywhere — no code, no confusion, no chaos.

[Other] Kill dev ports A lightweight cross-platform status bar app that monitors and manages development processes running on configurable ports. The app provides real-time process detection and allows you to kill individual processes or all processes at once.

[Other] Open-Ollama-WebUI makes running and exploring local AI model Open-Ollama-WebUI makes running and exploring local AI models effortless with a clean chat interface, model controls, and dynamic API support. - hamzaxinstitute/Open-Ollama-WebUI

[Other] Get specific information from texts ScholarSight is your intelligent research assistant, designed to help you analyze, synthesize, and extract key insights from academic papers and complex documents. Upload your PDFs, ask questions, and unlock a deeper understanding of your research.

[Testing] One click to convert product docs into automated mobile QA Quash is an AI-native mobile testing platform that automatically converts PRDs, Figma files, and app listings into ready-to-run test cases, so teams can ship faster without writing scripts. Early access is open, with code support coming soon.

[Other] Chrome extension for session recording & debugging Record user interactions, console logs, and network requests. Export sessions as JSON and replay them for comprehensive debugging and QA analysis.

[Other] Extract & copy clean css code Stop copying messy CSS from DevTools. Get production-ready code instead.

[API/SDK] Harmonized with life We provide API for physiological signal processing, enabling researchers and companies to analyze raw data such as PPG or ECG without building algorithms from scratch. Our goal: make biomedical signal analysis faster, reproducible, and accessible worldwide.

[API/SDK] Create AI powered chatbots in minutes Botennica lets you build AI chatbots trained on your own data—websites, files, or YouTube videos—and embed them easily. No coding needed, fully customizable, and affordable. Perfect for businesses, creators, or anyone wanting a smart personal chatbot.

[Other] AI-Powered Innovation Management: Figure out what to build AI-Powered Product Innovation Management Platform